Liisa Raud

Study Objectives: Sleep spindles are potential biomarkers for memory decline in aging. However, significant within-person variability in spindle attributes complicates their utility in predicting cognitive deterioration. This study aimed to uncover distinct spindle types and their relevance to memory decline using exploratory, data-driven clustering. Methods: Polysomnography was collected from younger (n = 43, ages 20–45 years) and older cognitively healthy adults (n = 34, ages 60–81 years). Clustering analysis was performed using multiple features and spatiotemporal context, irrespective of participant age. Results: Resulting clusters were hierarchically defined by the sleep stage, slow oscillation concurrence, and hemisphere. Stage N3 spindles (15%; predominantly coinciding with slow oscillations) formed a distinct group, followed by N2 spindles coinciding with slow oscillations (27%). Remaining N2 spindles were categorized into unilateral (41%) and bilateral clusters (17%). In older adults, there was a lower proportion of N2 bilateral spindles and a higher proportion of N2 spindles concurrent with slow oscillations. Lower proportion of N2 bilateral spindles was associated with better composite memory performance in younger adults, whereas higher spindle power, regardless of cluster belonging, was associated with reduced memory benefit from sleep compared with wakefulness. Conclusions: Our results indicate differing expression of spatiotemporal spindle clusters in older age, as well as intertwined dynamics between spindle propagation, slow oscillation concurrence, and frequency shifts in aging. In addition, spindle heterogeneity aligned with global sleep stage dynamics. These results emphasize the interconnectedness of spindle activity with overall sleep patterns, underscoring the importance of spatiotemporal context within and across sleep stages. Statement of Significance This study used data-driven clustering to explore sleep spindles as potential markers for age-related memory decline. We identified spindle clusters determined by sleep stage, slow oscillation concurrence, and hemisphere propagation. Notably, older adults showed altered expression of these clusters, indicating age-specific dynamics. Further research should focus on distinguishing spindle deterioration from broader sleep changes in older age. Such insights could pave the way for early detection and intervention strategies in cognitive decline, highlighting sleep’s crucial role in maintaining cognitive health and resilience in aging populations. These findings hold promise for developing targeted approaches to enhance mental wellness and quality of life in older adults.

Objectives Sleep spindles are potential biomarkers for memory decline in aging. However, significant within-person variability in spindle attributes complicates their utility in predicting cognitive deterioration. This study aimed to uncover distinct spindle types and their relevance to memory decline using data-driven clustering. Methods Polysomnography was collected from younger (n = 43, ages 20-45 years) and older cognitively healthy adults (n = 34, ages 60-81 years). Spindles were clustered into four groups using multiple features and spatiotemporal context, irrespective of participant age. Results Resulting clusters were hierarchically defined by the sleep stage, slow oscillation concurrence, and hemisphere. Stage N3 spindles (15%; predominantly coinciding with slow oscillations) formed a distinct group, followed by N2 spindles coinciding with slow oscillations (27%). Remaining N2 spindles were categorized into unilateral (41%) and bilateral clusters (17%). In older adults, there was a reduced proportion of N2 bilateral spindles and an increased proportion of N2 spindles concurrent with slow oscillations. Reduced proportion of N2 bilateral spindles was associated with better composite memory performance in younger adults, whereas higher spindle power, regardless of cluster belonging, was associated with reduced memory benefit from sleep compared with wakefulness. Conclusions Our results indicate differing expression of spatiotemporal spindle clusters in older age, as well as intertwined dynamics between spindle propagation, SO concurrence, and frequency shifts in ageing. In addition, spindle heterogeneity aligned with global sleep stage dynamics. These results emphasize the interconnectedness of spindle activity with overall sleep patterns, underscoring the importance of spatiotemporal context within and across sleep stages. Statement of significance This study used data-driven clustering to explore sleep spindles as potential markers for age-related memory decline. We identified spindle clusters determined by sleep stage, slow oscillation concurrence, and hemisphere propagation. Notably, older adults showed altered expression of these clusters, indicating age-specific dynamics. Further research should focus on distinguishing spindle deterioration from broader sleep changes in older age. Such insights could pave the way for early detection and intervention strategies in cognitive decline, highlighting sleep’s crucial role in maintaining cognitive health and resilience in aging populations. These findings hold promise for developing targeted approaches to enhance mental wellness and quality of life in older adults.

Inhibition in cognitive control has many implications. Behaviorally, the stop signal task is supposedly capturing inhibition of already initiated responses (response inhibition). In contrast, the flanker paradigm supposedly captures the inhibition of several competing responses (competitive inhibition). As the neural mechanisms for these behavioral phenomena are not clear, it begs the question of whether both response inhibition and competitive inhibition draw from a similar inhibitory resource pool and to what extent they might interact. In the current study, the potential interplay between inhibitory mechanisms was investigated in a combined stop-signal flanker task where (in-)congruent flankers were occasionally followed by stop signals. A multimodal task-setup was implemented allowing for examination of behavior, electromyography (EMG), electroencephalography (EEG), and pupillometry to assess different inhibition-related outcome measures.Model-based estimates of response inhibition speed (stop-signal reaction times; SSRTs) indicated an interaction with competitive inhibition, where stopping was faster in incongruent compared to congruent stop conditions. However, this interaction was not evident in physiological measures: neither stop-related EMG, EEG nor pupillometry measures showed such congruency modulations. Exploratory analyses showed that a larger pupillometry congruency effect was negatively associated with the congruency effect in SSRTs, suggesting that pupil dilation as a proxy for NE-LC activity might be linked to increased allocation of cognitive control. Taken together, our results do not provide clear evidence for an interaction between response inhibition and competitive inhibition.

Inhibition in cognitive control has many implications. Behaviorally, the stop signal task is supposedly capturing inhibition of already initiated responses (response inhibition). In contrast, the flanker paradigm supposedly captures the inhibition of several competing responses (competitive inhibition). As the neural mechanisms for these behavioral phenomena are not clear, it begs the question of whether both response inhibition and competitive inhibition draw from a similar inhibitory resource pool and to what extent they might interact. In the current study, the potential interplay between inhibitory mechanisms was investigated in a combined stop-signal flanker task where (in-)congruent flankers were occasionally followed by stop signals. A multimodal task-setup was implemented allowing for examination of behavior, electromyography (EMG), electroencephalography (EEG), and pupillometry to assess different inhibition-related outcome measures.Model-based estimates of response inhibition speed (stop-signal reaction times; SSRTs) indicated an interaction with competitive inhibition, where stopping was faster in incongruent compared to congruent stop conditions. However, this interaction was not evident in physiological measures: neither stop-related EMG, EEG nor pupillometry measures showed such congruency modulations. Exploratory analyses showed that a larger pupillometry congruency effect was negatively associated with the congruency effect in SSRTs, suggesting that pupil dilation as a proxy for NE-LC activity might be linked to increased allocation of cognitive control. Taken together, our results do not provide clear evidence for an interaction between response inhibition and competitive inhibition.

Lower episodic memory capability, as seen in development and aging compared with younger adulthood, may partly depend on lower brain network segregation. Here, our objective was twofold: (1) test this hypothesis using within- and between-network functional connectivity (FC) during episodic memory encoding and retrieval, in two independent samples (n=734, age 7-82 years). (2) Assess associations with age and the ability to predict memory comparing task-general FC and memory-modulated FC. In a multiverse-inspired approach, we performed tests across multiple analytic choices. Results showed that relationships differed based on these analytic choices, were often weak, and mainly present in the cohort with the most data. Significant relationships indicated that (i) memory-modulated FC predicted memory performance and associated with memory in an age-invariant manner. (ii) In line with the so- called neural dedifferentiation view, task-general FC showed lower segregation with higher age in adults which was associated with worse memory performance. In development, although there were only weak signs of a neural differentiation, that is, gradually higher segregation with higher age, we observed similar lower segregation-worse memory relationships. This age-invariant relationships between FC and episodic memory suggest that network segregation is pivotal for memory across the healthy lifespan. Declarations of interest none. Highlights Within- and between network functional connectivity predict memory performance. Multiverse-inspired analyses showed varying results depending on analytic choices. Memory associations particularly in the cohort with most data were age-invariant across the lifespan. Dedifferentiation might be better characterized as degrees of differentiation.

Even partly consolidated memories can be forgotten given sufficient time, but the brain activity associated with durability of episodic memory at different time scales remains unclear. Here, we aimed to identify brain activity associated with retrieval of partly consolidated episodic memories that continued to be remembered in the future. Forty-nine younger (20 to 38 years; 25 females) and 43 older adults (60 to 80 years, 25 females) were scanned with functional magnetic resonance imaging during associative memory retrieval 12 h post-encoding. Twelve hours is sufficient to allow short-term synaptic consolidation as well as early post-encoding replay to initiate memory consolidation. Successful memory trials were classified into durable and transient source memories based on responses from a memory test ~6 d post-encoding. Results demonstrated that successful retrieval of future durable vs. transient memories was supported by increased activity in a medial prefrontal and ventral parietal area. Individual differences in activation as well as the subjective vividness of memories during encoding were positively related to individual differences in memory performance after 6 d. The results point to a unique and novel aspect of brain activity supporting long-term memory, in that activity during retrieval of memories even after 12 h of consolidation contains information about potential for long-term durability.

Systems consolidation of new experiences into lasting episodic memories involves hippocampal–neocortical interactions. Evidence of this process is already observed during early post-encoding rest periods, both as increased hippocampal coupling with task-relevant perceptual regions and reactivation of stimulus-specific patterns following intensive encoding tasks. We investigate the spatial and temporal characteristics of these hippocampally anchored post-encoding neocortical modulations. Eighty-nine adults participated in an experiment consisting of interleaved memory task- and resting-state periods. We observed increased post-encoding functional connectivity between hippocampus and individually localized neocortical regions responsive to stimuli encountered during memory encoding. Post-encoding modulations were manifested as a nearly system-wide upregulation in hippocampal coupling with all major functional networks. The configuration of these extensive modulations resembled hippocampal–neocortical interaction patterns estimated from active encoding operations, suggesting hippocampal post-encoding involvement exceeds perceptual aspects. Reinstatement of encoding patterns was not observed in resting-state scans collected 12 h later, nor when using other candidate seed regions. The similarity in hippocampal functional coupling between online memory encoding and offline post-encoding rest suggests reactivation in humans involves a spectrum of cognitive processes engaged during the experience of an event. There were no age effects, suggesting that upregulation of hippocampal–neocortical connectivity represents a general phenomenon seen across the adult lifespan.

Memory encoding and retrieval are critical sub-processes of episodic memory. While the hippocampus is involved in both, its connectivity with the neocortex during memory processing in humans has been elusive. This is partially due to variations in demands in common memory tasks, which inevitably recruit cognitive processes other than episodic memory. Conjunctive analysis of data from different tasks with the same core elements of encoding and retrieval can reduce the intrusion of patterns related to subsidiary perceptual and cognitive processing. Leveraging data from two large-scale functional resonance imaging studies with different episodic memory tasks (514 and 237 participants), we identified core hippocampal-cortical networks active during memory processing. Anterior and posterior hippocampus had distinct connectivity profiles, which were stable across resting state and memory tasks. Whereas no encoding-specific connectome emerged across tasks, during retrieval hippocampal connectivity was increased with areas known to be active during recollection, including medial prefrontal, inferior parietal, and parahippocampal cortices. This indicates that the stable functional connectivity of the hippocampus along its longitudinal axis is superposed by increased functional connectivity with the recollection network during retrieval, while encoding connectivity likely reflects contextual factors.

Response inhibition is among the core constructs of cognitive control. It is notoriously difficult to quantify from overt behavior, since the outcome of successful inhibition is the lack of a behavioral response. Currently, the most common measure of action stopping, and by proxy response inhibition, is the model-based stop signal reaction time (SSRT) derived from the stop signal task. Recently, partial response electromyography (prEMG) has been introduced as a complementary physiological measure to capture individual stopping latencies. PrEMG refers to muscle activity initiated by the go signal that plummets after the stop signal before its accumulation to a full response. Whereas neither the SSRT nor the prEMG is an unambiguous marker for neural processes underlying response inhibition, our analysis indicates that the prEMG peak latency is better suited to investigate brain mechanisms of action stopping. This study is a methodological resource with a comprehensive overview of the psychometric properties of the prEMG in a stop signal task, and further provides practical tips for data collection and analysis.